Modeling Star Formation as a Markov Process in a Supersonic Gravoturbulent Medium

TL;DR

This paper models star formation in turbulent molecular clouds using a Markov process, demonstrating that a simple Langevin equation can replicate complex simulation results including gravity effects.

Contribution

It introduces a Markov process model with a simple Langevin equation that captures the evolution of density PDFs and collapse rates in turbulent, self-gravitating media.

Findings

The rate of density change increases at higher densities.

A two-parameter Langevin equation reproduces simulation results.

Including gravity in the model matches collapse rates in simulations.

Abstract

Molecular clouds exhibit lognormal probability density functions (PDF) of mass densities, which are thought to arise as a consequence of isothermal, supersonic turbulence. Star formation is then widely assumed to occur in perturbations in which gravitational collapse is faster than the rate of change due to turbulent motions. Here we use direct numerical simulations to measure this rate as a function of density for a range of turbulent Mach numbers, and show it is faster at high densities than at low densities. Furthermore, we show that both the density PDF and rate of change arise naturally in a simple model of turbulence as a continuous Markov process. The one-dimensional Langevin equation that describes this evolution depends on only two parameters, yet it captures the full evolution seen in direct three-dimensional simulations. If it is modified to include gravity, the Langevin equation also reproduces the rate of material collapsing to high densities seen in turbulent simulations including self-gravity. When generalized to include both temperature and density, similar analyses are likely applicable throughout astrophysics.